Evidence map›Paper›PMID 37666866›Full record

Observational studyScientific reports2023

Identification of potential new COVID-19 treatments via RWD-driven drug repurposing.

Yun Liao

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.6field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Yun LiaoLife Sciences, OptumInsight/OptumRx, UnitedHealth Group Inc, Basking Ridge, NJ, USA. yun.liao@optum.com.
UnitedHealth Group (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

By utilizing Optum Life Sciences Claims Data, we constructed Real World Data (RWD) cohorts comprising over 3 million patients and simulated a clinical trial observational study design to evaluate over 200 FDA-approved drugs with COVID-19 repurposing potential, and identified a dozen candidates exhibiting significant reduction in the odds of severe COVID-19 outcomes such as death, intensive care unit (ICU) admission, hospitalization and pneumonia. Notably, certain drug combinations demonstrated effects comparable to those of COVID-19 vaccines. Furthermore, our study revealed a novel finding: a quantitative linear relationship between COVID-19 outcomes and overall patient health risks. This discovery enabled a more precise estimation of drug efficacy using the risk adjustment. The top performing drugs identified include emtricitabine, tenofovir, folic acid, progesterone, estradiol, epinephrine, disulfiram, nitazoxanide and some drug combinations including aspirin-celecoxib.

Indexed as

COVID-19AspirinCOVID-19 Drug TreatmentCOVID-19 VaccinesDrug RepositioningHumansAspirinCOVID-19 Vaccines

Identifiers

PMID37666866
PMCPMC10477169
OpenAlexW4386424031

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.